Refactor operator python test framework and add sum operator by QiJune · Pull Request #3882 · PaddlePaddle/Paddle

QiJune · 2017-09-05T11:36:59Z

Fix operator python test needs to support duplicate inputs/outputs #3886, support duplicate inputs/outputs.
implement sum operator to test the refactored operator python test framework.
reduce codes and simplify user's configuration.

wangkuiyi

A few comments. Otherwise LGTM!

wangkuiyi · 2017-09-06T07:04:44Z

paddle/framework/operator.h


  template <typename T>
-  std::vector<const T*> MultiOutput(const std::string& name) const {
+  std::vector<T*> MultiOutput(const std::string& name) const {


I am not sure, should we name this DuplicableOutput?

Yes, I think DuplicableOutput is more accerate

wangkuiyi · 2017-09-06T07:06:05Z

paddle/operators/sum_op.h

+using Tensor = framework::Tensor;
+template <typename T, int MajorType = Eigen::RowMajor,
+          typename IndexType = Eigen::DenseIndex>
+using EigenVector = framework::EigenVector<T, MajorType, IndexType>;


Let us don't use using in header files. https://google.github.io/styleguide/cppguide.html#Namespaces

I think we can move this using directive into class SumKernel.

Now, all the operators have the same problem. I will make another pr to move using in head file in all operators

reyoung · 2017-09-06T16:59:22Z

paddle/framework/operator.h

+    return result;
+  }
+
+  const std::vector<std::string> OutputsNames() const {


Is that same as OutputVars method?

It seems the same. I will remove this method

reyoung · 2017-09-06T17:00:55Z

paddle/operators/sum_op.cc

+    auto ins = ctx.MultiInput<framework::Tensor>("X");
+    auto *out = ctx.Output<framework::Tensor>("Out");
+    int N = ins.size();
+


Here should check all dims of inputs are same.

reyoung · 2017-09-06T17:02:33Z

paddle/operators/sum_op.h

+    result.device(place) = in;
+    for (int i = 1; i < N; i++) {
+      auto in = EigenVector<T>::Flatten(*(ins[i]));
+      result.device(place) = result + in;


This implementation is very slow because it starts many GPU kernels. Maybe we could have a better implementation.

Yes, I will make a more efficient implementation in next PR. This PR is mainly focus on supporting multi-inputs/outputs.

reyoung · 2017-09-06T17:05:19Z

python/paddle/v2/framework/tests/op_test.py

+import paddle.v2.framework.core as core
+from paddle.v2.framework.op import Operator
+
+


Maybe "@Grad" should be a global variable.

reyoung · 2017-09-06T17:06:12Z

python/paddle/v2/framework/tests/op_test.py

+
+    for ins in Operator.get_op_inputs(op_type):
+        in_name = ins[0]
+        in_dup = ins[1]


for in_name, in_dup in Operator.get_op_inputs(op_type):

reyoung · 2017-09-06T17:09:10Z

python/paddle/v2/framework/tests/test_sum_op.py

+        x0 = np.random.random((3, 4)).astype('float32')
+        x1 = np.random.random((3, 4)).astype('float32')
+        x2 = np.random.random((3, 4)).astype('float32')
+        self.inputs = {"X": {"x0": x0, "x1": x1, "x2": x2}}


I think maybe the user does not want to specify names about x0, x1, x2.

Just,

self.inputs = { "X": [x0, x1, x2] }

is OK.

Just,

self.inputs = {
"X": [x0, x1, x2]
}
is OK.

If so, how to generate the multi-inputs name for "x0", "x1" and "x2"? Generate these names automatically according to 'X'?

@reyoung @qingqing01 In grad check process, we can chose a specific input. Such as

self.check_grad(["x0"], "Out")

So, explicitly set a name is more flexible.

reyoung · 2017-09-06T17:12:01Z

python/paddle/v2/framework/tests/op_test.py

+                tensor = var.get_tensor()
+                kwargs[out_name].append(out_name)
+
+    # for attr_name in Operator.get_op_attr_names(op_type):


So where are the attributes?

qingqing01 · 2017-09-07T12:45:56Z

python/paddle/v2/framework/tests/op_test.py

+
+
+def remove_grad_var_name(var_name):
+    return var_name[0:-5]


The remove_grad_var_name is not used?

I will remove it.

qingqing01 · 2017-09-07T12:48:04Z

python/paddle/v2/framework/tests/op_test.py

+                    kwargs[in_name].append(sub_in_name)
+            else:
+                var = scope.new_var(in_name)
+                tensor = var.get_tensor()


Remove tensor = var.get_tensor(), only need to new var.

Also remove line 28.

Yes, I will remove it later

qingqing01 · 2017-09-07T12:48:19Z

python/paddle/v2/framework/tests/op_test.py

+                    kwargs[out_name].append(sun_in_name)
+            else:
+                var = scope.new_var(out_name)
+                tensor = var.get_tensor()


remove line 44 and line 48

qingqing01 · 2017-09-07T12:50:28Z

python/paddle/v2/framework/tests/op_test.py

+    return Operator(op_type, **kwargs)
+
+
+def set_input(scope, op, inputs, place):


The set_input can be reused in create_op.

qingqing01 · 2017-09-07T12:57:21Z

python/paddle/v2/framework/tests/op_test.py

+        # add delta to it, run op and then get the sum of the result tensor.
+        x_pos = origin + delta
+        tensor_to_check.set_float_element(i, x_pos)
+        y_pos = get_output()


after line 136, need to add: @reyoung

tensor_to_check.set_float_element(i, origin)

The gradient_check.py does not have this line.

@qingqing01 It seems that it is not needed.

qingqing01 · 2017-09-07T12:58:35Z

python/paddle/v2/framework/tests/op_test.py

+        var.get_tensor()
+    for output in backward_op.outputs_names():
+        var = scope.new_var(output)
+        var.get_tensor()


remove line 155 and line 158

qingqing01 · 2017-09-07T13:02:54Z

python/paddle/v2/framework/tests/test_sum_op.py

+        x0 = np.random.random((3, 4)).astype('float32')
+        x1 = np.random.random((3, 4)).astype('float32')
+        x2 = np.random.random((3, 4)).astype('float32')
+        self.inputs = {"X": {"x0": x0, "x1": x1, "x2": x2}}


Just,

self.inputs = {
"X": [x0, x1, x2]
}
is OK.

If so, how to generate the multi-inputs name for "x0", "x1" and "x2"? Generate these names automatically according to 'X'?

qingqing01 · 2017-09-07T13:15:42Z

python/paddle/v2/framework/tests/op_test.py

+        in_dup = ins[1]
+        if in_name in inputs:
+            kwargs[in_name] = []
+            if in_dup:


在C++ Operators里面，是否为duplicate，inputs/outputs的存储格式都一样，为：

using VariableNameMap = std::map<std::string, std::vector<std::string>>;

所以，Python里也可以统一格式，不用区分是否in_dup, 但会导致如下：

一个输入写成： inputs = {'X': ['X']} (一个也得写成['X'])

多个输入(假如2个)写成： inputs = {'X': ['X1', 'X2']}

(这里假设ProtoMaker里注册的Key为“X”)

这样很多地方都不用if in_dup: else判断了吧。

确实是的。但大部分的operator不是duplicate的输入，可以让用户的配置稍微简单一些。
现在的处理逻辑是：
1 如果是一般的输入输出，那么用户直接给一个numpy array就可以了，测试框架会自动把key当做variable的名字。好处是用户的配置稍微简化一些。
2 如果是duplicate的输入输出，那么用户需要给定一个 {"name1": array1, "name2": array2}的字典。测试框架会拿到每一个名字。好处是用户可以指定check具体哪一个输入的grad，比如name1的值发生变化，对输出结果的变化。

reyoung

LGTM, except gradient of sum could be composed by many identity operators.

QiJune · 2017-09-11T03:16:22Z

@reyoung I will merge this PR first, and will refine both forward and backward implementation of sum operator in next PR.

QiJune added 2 commits September 5, 2017 19:32

refactor operator python test and add sum operator

f314330

fix bug

a22606c

QiJune requested review from jacquesqiao, qingqing01 and reyoung September 5, 2017 12:54

qingqing01 added the OpPorting label Sep 5, 2017

wangkuiyi reviewed Sep 6, 2017

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reyoung reviewed Sep 6, 2017

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qingqing01 reviewed Sep 7, 2017

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QiJune added 4 commits September 8, 2017 14:54

follow comments

f50e36e

merge baidu/develop

090b811

fix gou test bug

15627e4

fix code style

c019288

reyoung approved these changes Sep 11, 2017

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QiJune merged commit c169669 into PaddlePaddle:develop Sep 11, 2017

		import paddle.v2.framework.core as core
		from paddle.v2.framework.op import Operator

		return Operator(op_type, **kwargs)


		def set_input(scope, op, inputs, place):

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